scholarly journals 1961–1990 monthly high-resolution solar radiation climatologies for Italy

2012 ◽  
Vol 8 (1) ◽  
pp. 19-25 ◽  
Author(s):  
J. Spinoni ◽  
M. Brunetti ◽  
M. Maugeri ◽  
C. Simolo
Keyword(s):  
High Resolution ◽  
Solar Radiation ◽  
Normal Values ◽  
Sunshine Duration ◽  
Global Radiation ◽  
Data Set ◽  
Sparse Network ◽  
Duration Data ◽  
Atmospheric Turbidity ◽  
Preliminary Version

Abstract. We present a methodology for estimating solar radiation climatologies from a sparse network of global radiation and/or sunshine duration records: it allows to obtain high-resolution grids of monthly normal values for global radiation (and for the direct and diffuse components), atmospheric turbidity, and surface absorbed radiation. We discuss the application of the methodology to a preliminary version of an Italian global radiation and sunshine duration data set, which completion is still in progress and present the resulting 1961–1990 monthly radiation climatologies.

SARAH-3 – a new satellite-based Climate Data Record of Surface Solar Radiation parameters

2021 ◽  
Author(s):  
Uwe Pfeifroth ◽  
Jaqueline Drücke ◽  
Jörg Trentmann ◽  
Rainer Hollmann
Keyword(s):  
Solar Radiation ◽  
Sunshine Duration ◽  
Global Radiation ◽  
Surface Radiation ◽  
Climate Data ◽  
Regional Variability ◽  
Surface Solar Radiation ◽  
Data Set ◽  
Data Record ◽  
Climate Data Record

<p class="western"><span lang="en-US">The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates and distributes high quality long-term climate data records (CDR) of energy and water cycle parameters, which are freely available.</span></p> <p class="western"><span lang="en-US">In 2022, a new version of the “Surface Solar Radiation data set – Heliosat” will be released: SARAH-3. As the previous editions, the SARAH-3 climate data record is based on satellite observations from the first and second METEOSAT generations and provides various surface radiation parameters, including global radiation, direct radiation, sunshine duration, photosynthetic active radiation and others. SARAH-3 covers the time period 1983 to 2020 and offers 30-minute instantaneous data as well as daily and monthly means on a regular 0.05° x 0.05° lon/lat grid.</span></p> <p class="western" align="left"><span lang="en-US">In this presentation, an overview of the SARAH climate data record and their applications will be given. A focus will be on the SARAH-3 developments and validation with surface reference observations. Further, SARAH-3 will be used for a first analysis of the climate variability and potential trends of global radiation in Europe during the last decades. </span><span lang="en-US">The data record reveals that there is an increasing trend of surface solar radiation in Europe during the last decades, which is superimposed by decadal and regional variability.</span></p>

Testing the spatial applicability of the Johnson–Woodward method for estimating solar radiation from sunshine duration data

2008 ◽  
Vol 148 (3) ◽  
pp. 466-480 ◽  
Author(s):  
D.G. Miller ◽  
M. Rivington ◽  
K.B. Matthews ◽  
K. Buchan ◽  
G. Bellocchi
Keyword(s):  
Solar Radiation ◽  
Sunshine Duration ◽  
Duration Data

scholarly journals Merging ground-based sunshine duration observations with satellite cloud and aerosol retrievals to produce high-resolution long-term surface solar radiation over China

2021 ◽  
Vol 13 (3) ◽  
pp. 907-922
Author(s):  
Fei Feng ◽  
Kaicun Wang
Keyword(s):  
Standard Deviation ◽  
High Resolution ◽  
Solar Radiation ◽  
Spatial Resolution ◽  
Sunshine Duration ◽  
Ordinary Least Squares ◽  
Cloud Fraction ◽  
Surface Solar Radiation ◽  
The Impact

Abstract. Although great progress has been made in estimating surface solar radiation (Rs) from meteorological observations, satellite retrieval, and reanalysis, getting best-estimated long-term variations in Rs are sorely needed for climate studies. It has been shown that Rs data derived from sunshine duration (SunDu) can provide reliable long-term variability, but such data are available at sparsely distributed weather stations. Here, we merge SunDu-derived Rs with satellite-derived cloud fraction and aerosol optical depth (AOD) to generate high-spatial-resolution (0.1∘) Rs over China from 2000 to 2017. The geographically weighted regression (GWR) and ordinary least-squares regression (OLS) merging methods are compared, and GWR is found to perform better. Based on the SunDu-derived Rs from 97 meteorological observation stations, which are co-located with those that direct Rs measurement sites, the GWR incorporated with satellite cloud fraction and AOD data produces monthly Rs with R2=0.97 and standard deviation =11.14 W m−2, while GWR driven by only cloud fraction produces similar results with R2=0.97 and standard deviation =11.41 W m−2. This similarity is because SunDu-derived Rs has included the impact of aerosols. This finding can help to build long-term Rs variations based on cloud data, such as Advanced Very High Resolution Radiometer (AVHRR) cloud retrievals, especially before 2000, when satellite AOD retrievals are not unavailable. The merged Rs product at a spatial resolution of 0.1∘ in this study can be downloaded at https://doi.org/10.1594/PANGAEA.921847 (Feng and Wang, 2020).

scholarly journals General Formula for Estimation of Monthly Mean Global Solar Radiation in Different Climates on the South and North Coasts of Iran

2007 ◽  
Vol 2007 ◽  
pp. 1-7 ◽  
Author(s):  
Ali A. Sabziparvar
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
General Formula ◽  
Sunshine Duration ◽  
Global Radiation ◽  
Global Solar Radiation ◽  
Maximum Temperature ◽  
The South ◽  
Coastal Regions ◽  
Different Climates

Using sunshine duration, cloud cover, relative humidity, average of maximum temperature, and ground albedo as the input of several radiation models, the monthly average daily solar radiation on horizontal surface in various coastal cities of the South (25.23∘N) and the North (38.42∘N) of Iran are estimated. Several radiation models are tested and further are revised by taking into consideration the effects of relative humidity, ground albedo, and Sun-Earth distance. Model validation is performed by using up to 13 years (1988–2000) of daily solar observations. Errors are calculated using MBE, MABE, MPE, and RMSE statistical criteria (see nomenclature) and further a general formula which estimates the global radiation in different climates of coastal regions is suggested. The proposed method shows a good agreement (less than7%deviation) with the long-term pyranometric data. In comparison with other works done so far, the suggested method performs a higher degree of accuracy for those of two regions. The model results can be extended to other locations in coastal regions where solar data are not available.

scholarly journals SARAH-3 - a new satellite-based Cimate Data Record for surface radiation parameters from the CM SAF

2021 ◽  
Author(s):  
Uwe Pfeifroth ◽  
Jaqueline Drücke ◽  
Jörg Trentmann ◽  
Rainer Hollmann
Keyword(s):  
Water Cycle ◽  
Sunshine Duration ◽  
Global Radiation ◽  
Surface Radiation ◽  
Climate Data ◽  
Surface Solar Radiation ◽  
Data Set ◽  
Time Period ◽  
Data Record ◽  
Climate Data Record

<p>The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates and distributes high quality long-term climate data records (CDR) of energy and water cycle parameters, which are freely available.</p><p>In fall 2021, a new version of the “Surface Solar Radiation data set – Heliosat” will be released: SARAH-3. As the previous editions, the SARAH-3 climate data record is based on satellite observations from the first and second METEOSAT generations and provides various surface radiation parameters, including global radiation, direct radiation, sunshine duration, photosynthetic active radiation and others. SARAH-3 covers the time period 1983 to 2020 and offers 30-minute instantaneous data as well as daily and monthly means on a regular 0.05° x 0.05° lon/lat grid.</p><p>In this presentation, an overview of the SARAH climate data record and their applications will be provided. A focus will be on the SARAH-3 developments and improvements (i.e. improved consideration of snow-covered surfaces). First validation results of the new Climate Data Record using surface reference observations will be presented. Further, SARAH-3 will be used for the analysis of the climate variability in Europe during the last decades.</p><p>. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .</p>

PROCESSING SUNSHINE DURATION MEASUREMENTS FOR THE ASSESSMENT OF SOLAR RADIATION IN CLIMATIC REGIONS OF THE CENTRAL AFRICAN REPUBLIC

2022 ◽  
pp. 1-27
Author(s):  
Venant Sorel Chara-Dackou ◽  
Donatien Njomo ◽  
Mahamat Hassane Babikir ◽  
mbouombouo ngapouth ibrahim ◽  
Gboulie Pofoura Aicha sidica ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Large Scale ◽  
Central African Republic ◽  
Polynomial Regression ◽  
Least Squares Method ◽  
Sunshine Duration ◽  
Global Radiation ◽  
Diffuse Radiation ◽  
Ordinary Least Squares ◽  
Climatic Regions

Abstract The objectives of this work carried out in the Central African Republic are to propose new correlations between the components of solar radiation and the sunshine duration on a horizontal surface on the ground, and then to make an evaluation of the solar potential in the cities of Bambari, Birao and Bangui. Polynomial regression models were used and their parameters were estimated by the ordinary least squares method. A statistical evaluation allowed us to compare the performance of the models. The best correlations are then used to estimate the global and diffuse radiation. In the city of Birao, the estimated global radiation is around 6 kWh/m2.j and the diffuse radiation around 2 kWh/m2.j ; in Bambari the global radiation is around 5.4 kWh/m2.j and the diffuse around 2.3 kWh/m2.j ; in Bangui the global radiation is around 5 kWh/m2.j and the diffuse radiation around 2.3 kWh/m2.j. The potential solar in all these regions is very favorable for small and large-scale solar photovoltaic applications.

scholarly journals PREDICTING SOLAR RADIATION FOR TROPICAL ISLANDS FROM RAINFALL DATA

2016 ◽  
Vol 9 (2) ◽  
pp. 109-118 ◽  
Author(s):  
Sisuru Sendanayake ◽  
Nandika Miguntanna ◽  
M. T. R. Jayasinghe
Keyword(s):  
Sri Lanka ◽  
Solar Radiation ◽  
Meteorological Parameters ◽  
Sunshine Duration ◽  
Global Radiation ◽  
Incident Radiation ◽  
Cloud Formation ◽  
Weather Data ◽  
Tropical Islands ◽  
The Mean

There are many correlations developed to predict incident solar radiation at a given location developed based on geographical and meteorological parameters. However, all correlations depend on accurate measurement and availability of weather data such as sunshine duration, cloud cover, relative humidity, maximum and minimum temperatures etc, which essentially is a costly exercise in terms of equipment and labour. Sri Lanka being a tropical island of latitudinal change of only 30 along the length of the country, the meteorological factors govern the amount of incident radiation. Considering the cloud formation and wind patterns over Sri Lanka as well as the seasonal rainfall patterns, it can be observed that the mean number of rainy days can be used to predict the monthly average daily global radiation which can be used for calculations in solar related activities conveniently.

scholarly journals PREDICTING SOLAR RADIATION FOR TROPICAL ISLANDS FROM RAINFALL DATA

2016 ◽  
Vol 9 (2) ◽  
pp. 109-118 ◽  
Author(s):  
Sisuru Sendanayake ◽  
Nandika Miguntanna ◽  
M. T. R. Jayasinghe
Keyword(s):  
Sri Lanka ◽  
Solar Radiation ◽  
Meteorological Parameters ◽  
Sunshine Duration ◽  
Global Radiation ◽  
Incident Radiation ◽  
Cloud Formation ◽  
Weather Data ◽  
Tropical Islands ◽  
The Mean

There are many correlations developed to predict incident solar radiation at a given location developed based on geographical and meteorological parameters. However, all correlations depend on accurate measurement and availability of weather data such as sunshine duration, cloud cover, relative humidity, maximum and minimum temperatures etc, which essentially is a costly exercise in terms of equipment and labour. Sri Lanka being a tropical island of latitudinal change of only 30 along the length of the country, the meteorological factors govern the amount of incident radiation. Considering the cloud formation and wind patterns over Sri Lanka as well as the seasonal rainfall patterns, it can be observed that the mean number of rainy days can be used to predict the monthly average daily global radiation which can be used for calculations in solar related activities conveniently.

scholarly journals A 16-year dataset (2000–2015) of high-resolution (3 hour, 10 km) global surface solar radiation

2019 ◽  
Author(s):  
Wenjun Tang ◽  
Kun Yang ◽  
Jun Qin ◽  
Xin Li ◽  
Xiaolei Niu
Keyword(s):  
High Resolution ◽  
Solar Radiation ◽  
Radiant Energy ◽  
Reanalysis Data ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Mean Bias Error ◽  
Surface Solar Radiation ◽  
Data Set ◽  
Global Surface

Abstract. The recent release of the International Satellite Cloud Climatology Project (ISCCP) HXG cloud products and new ERA5 reanalysis data enabled us to produce a global surface solar radiation (SSR) dataset: a 16-year (2000–2015) high-resolution (3 h, 10 km) global SSR dataset with an improved physical parameterization scheme. The main inputs were cloud optical depth from ISCCP-HXG cloud products, the water vapor, surface pressure and ozone from ERA5 reanalysis data, and albedo and aerosol from Moderate Resolution Imaging Spectroradiometer (MODIS) products. The estimated SSR data was evaluated against surface observations measured at 42 stations of the Baseline Surface Radiation Network (BSRN) and 90 radiation stations of the China Meteorological Administration (CMA). Validation against the BSRN data indicated that the mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (R) for the instantaneous SSR estimate at 10 km scale were −11.5 W m−2, 113.5 W m−2, and 0.92, respectively. The error was clearly reduced when the data were upscaled to 90 km; RMSE decreased to 93.4 W m−2 and R increased to 0.95. For daily SSR estimates at 90 km scale, the MBE, RMSE and R at the BSRN were −5.8 W m−2, 33.1 W m−2 and 0.95, respectively. These error metrics at the CMA radiation stations were 2.1 W m−2, 26.9 W m−2 and 0.95, respectively. Comparisons with other global satellite radiation products indicated that our SSR estimates were generally better than those of the ISCCP flux dataset (ISCCP-FD), the global energy and water cycle experiment surface radiation budget (GEWEX-SRB), and the Earth's Radiant Energy System (CERES). Our SSR dataset will contribute to the land-surface process simulations and the photovoltaic applications in the future. The data set is available at https://doi.org/10.11888/Meteoro.tpdc.270112 (Tang, 2019).

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